class_docstr: Base object for all settings, which is a pickable dict.
  For user-specified functions, the settings dictionary might include functions as a key.
  These functions unfortunately can not easily be transported to workers in multiprocessing
  or multi-cloud setups, as they are not pickable by default.
  Therefore, we change the pickle-behavior of this class and use cloudpickle for
  pickling and unpickling the keys of the dictionary, before pickling the full object.
  cloudpickle is able to pickle much more functions than pickle can and pickle will
  only see the already encoded keys (not the raw functions).
docstr: Called on un-pickling. cloudunpickle the keys again
docstr_tok: ["Called","on","un-pickling",".","cloudunpickle","the","keys","again"]
code: def __setstate__(self, state):
      """Called on un-pickling. cloudunpickle the keys again"""
      state = {
          cloudpickle.loads(key): value for key, value in state.items()
      }
      # please note that the internal dictionary is stored as "data" in the UserDict
      self.__dict__.update(data=state)
  
imports: import logging
  from builtins import range
  from collections import UserDict
  from inspect import getfullargspec
  from itertools import product
  import cloudpickle
  import pandas
  from tsfresh.feature_extraction import feature_calculators
  from tsfresh.utilities.string_manipulation import get_config_from_string
label_desc: Use image node_id 2 for calling the PickableSettings obj's underlying member method code with example usage: obj.__setstate__(state) without return types